Relative contribution of COVID-19 vaccination and SARS-CoV-2 infection to population-level seroprevalence of SARS-CoV-2 spike antibodies in a large integrated health system.

Background: Understanding the relative contributions of SARS-CoV-2 infection-induced and vaccine- induced seroprevalence is key to measuring overall population-level seroprevalence and help guide policy decisions. Methods: Using a series of six population-based cross-sectional surveys conducted among persons aged ≥7 years in a large health system with over 4.5 million members between May 2021 and April 2022, we combined data from the electronic health record (EHR), an electronic survey and SARS-CoV-2 spike antibody binding assay, to assess the relative contributions of infection and vaccination to population- level SARS-CoV-2 seroprevalence. EHR and survey data were incorporated to determine spike antibody positivity due to SARS-CoV-2 infection and COVID-19 vaccination. We used sampling and non-response weighting to create population-level estimates. Results: We enrolled 4,319 persons over six recruitment waves. SARS-CoV-2 spike antibody seroprevalence increased from 83.3% (CI 77.0-88.9) in May 2021 to 93.5% (CI 89.5-97.5) in April 2022. By April 2022, 68.5% (CI 61.9-74.3) of the population was seropositive from COVID-19 vaccination only, 13.9% (10.7-17.9) from COVID-19 vaccination and prior diagnosed SARS-CoV-2 infection, 8.2% (CI 4.5- 14.5) from prior diagnosed SARS-CoV-2 infection only and 2.9% (CI 1.1-7.6) from prior undiagnosed SARS-CoV-2 infection only. We found high agreement (≥97%) between EHR and survey data for ascertaining COVID-19 vaccination and SARS-CoV-2 infection status. Conclusions: By April 2022, 93.5% of persons had detectable SARS-CoV-2 spike antibody, predominantly from COVID-19 vaccination. In this highly vaccinated population and over 18 months into the pandemic, SARS-CoV-2 infection without COVID-19 vaccination was a small contributor to overall population-level seroprevalence. Article summary: By April 2022, >93% of people had antibodies to SARS-CoV-2 with COVID-19 vaccination as the main driver of overall population-level seroprevalence in our healthcare system. SARS-CoV-2 infection without vaccination made a small contribution to population-level seroprevalence in our healthcare system.

Concurrent Sexually Transmitted Infections with Mpox Infections: A Brief Review.

Mpox is a viral zoonotic infection endemic to countries in Central and West Africa. The outbreak that began in May 2022 is novel for its global spread and transmission through sexual encounters. Research of this outbreak shows a high rate of concurrent sexually transmitted infections (STIs) in patients with mpox, highlighting the need to consider STIs in mpox management, and to raise awareness of historically high levels of STIs caused by inadequacies in sexual health care. It is critical to prioritize sexual health and address health disparities to control current transmission of infections and prevent future outbreaks.

Latent Tuberculosis Infection Testing Practices in a Large US Integrated Healthcare System.

BACKGROUND: Tuberculosis (TB) is a public health threat, with >80% of active TB in the United States occurring due to reactivation of latent TB infection (LTBI). We may be underscreening those with high risk for LTBI and overtesting those at lower risk. A better understanding of gaps in current LTBI testing practices in relation to LTBI test positivity is needed. METHODS: This study, conducted between 1 January 2008 and 31 December 2019 at Kaiser Permanente Southern California, included individuals aged ≥18 years without a history of active TB. We examined factors associated with LTBI testing and LTBI positivity. RESULTS: Among 3 816 884 adults (52% female, 37% White, 37% Hispanic, mean age 43.5 years [standard deviation, 16.1]), 706 367 (19%) were tested for LTBI, among whom 60 393 (9%) had ≥1 positive result. Among 1 211 971 individuals who met ≥1 screening criteria for LTBI, 210 025 (17%) were tested for LTBI. Factors associated with higher adjusted odds of testing positive included male sex (1.32; 95% confidence interval, 1.30-1.35), Asian/Pacific Islander (2.78, 2.68-2.88), current smoking (1.24, 1.20-1.28), diabetes (1.13, 1.09-1.16), hepatitis B (1.45, 1.34-1.57), hepatitis C (1.54, 1.44-1.66), and birth in a country with an elevated TB rate (3.40, 3.31-3.49). Despite being risk factors for testing positive for LTBI, none of these factors were associated with higher odds of LTBI testing. CONCLUSIONS: Current LTBI testing practices may be missing individuals at high risk of LTBI. Additional work is needed to refine and implement screening guidelines that appropriately target testing for those at highest risk for LTBI.

Prior Screening for Latent Tuberculosis Among Patients Diagnosed With Tuberculosis Disease: Missed Opportunities?

Background: California has the largest number of tuberculosis (TB) disease cases in the United States. This study in a large California health system assessed missed opportunities for latent tuberculosis (LTBI) screening among patients with TB disease. Methods: Kaiser Permanente Southern California patients who were ≥18 years old with membership for ≥24 months during the study period from 1 January 2008 to 31 December 2019 were included. Prior LTBI test (tuberculin skin test or interferon-γ release assay) or diagnosis code prior to TB disease diagnosis was assessed among patients with observed TB disease (confirmed by polymerase chain reaction and/or culture). In the absence of current treatment practices, more patients screened for LTBI may have developed TB disease. We estimated hypothetical TB disease cases prevented by multiplying LTBI progression rates by the number of LTBI-positive patients prescribed treatment. Results: A total of 1289 patients with observed TB disease were identified; 148 patients were LTBI positive and 84 were LTBI negative. Patients not prescreened for LTBI made up 82.0% of observed TB disease cases (1057/1289). Adding the hypothetical maximum estimate for prevented cases decreased the percentage of patients who were not prescreened for LTBI to 61.7% [1057/(1289 + 424)]. Conclusions: One-fifth of patients were screened for LTBI prior to their active TB diagnosis. Assuming the upper bound of cases prevented through current screening, almost 62% of TB disease patients were never screened for LTBI. Future work to elucidate gaps in LTBI screening practices and to identify opportunities to improve screening guidelines is needed.

Asthma and COVID-19 Outcomes: A Prospective Study in a Large Health Care Delivery System.

Introduction: Previous studies on the outcomes of asthma and COVID-19 have shown inconsistent results. This study aimed to elucidate the association between asthma and COVID-19 outcomes. Methods: We conducted a prospective study with a large health plan to compare the incidence of COVID-19 infection, hospitalization and ICU admission in a cohort of 41,282 patients with asthma and a 1:1 age-, sex-, and race-ethnicity-matched cohort without asthma across the following pandemic periods: pre-Delta (03/01/2020 to 05/31/2021), Delta (06/01/2021 to 12/31/2021), and Omicron (01/01/2022 to 08/13/2022). Demographic factors, comorbidities, COVID-19 test results, inpatient utilization, and COVID-19 vaccination status were collected from electronic health records. Results: Subjects with asthma were more likely than controls to undergo COVID-19 testing during the three pandemic periods and were less likely to test positive in the Omicron period (fully adjusted odds ratio=0.92; 95% CI=0.86-0.98; p=0.01). Relative to controls, patients with asthma had an increased risk of hospitalization for COVID-19 (fully adjusted hazard ratio=1.33; 95% CI=1.08-1.64; p=0.01) and borderline significant (p=0.05) higher rates of ICU admissions in the pre-delta period but not during the delta or Omicron periods. The increased risk of COVID-19 hospitalization associated with asthma was more pronounced in patients with severe asthma and in women compared with men. None of the associations were significantly modified by vaccination status. Conclusion: Asthma was associated with a lower risk of COVID-19 infection but only during the Omicron period. Asthma was an independent risk factor for hospitalization for COVID-19 in the pre-delta period and this association was stronger for severe asthma and in women.

Real-World Evidence to Supplement Randomized Clinical Trials: Tocilizumab for Severe COVID-19 Pneumonia vs. a Cohort Receiving Standard of Care.

Randomized controlled trials (RCTs) remain the gold standard for evaluating treatment efficacy, but real-world evidence can supplement RCT results. Tocilizumab was not found to reduce 28-day mortality in a phase III, double-blind, placebo-controlled trial (COVACTA) among hospitalized patients with severe coronavirus disease 2019 (COVID-19) pneumonia. We created a real-world external comparator arm mirroring the COVACTA trial to confirm findings and assess the feasibility of using an external comparator arm to supplement an RCT. Eligible COVACTA participants in both the tocilizumab treatment and placebo arms were matched 1:1 using propensity score matching to persons without tocilizumab exposure in an external comparator arm. Adjusted Cox proportional hazard models estimated differences in 28-day mortality comparing COVACTA participants to matched external comparator arm participants. Patients in the COVACTA tocilizumab treatment arm had a similar risk of death compared with patients in the external comparator arm (hazard ratio (HR): 1.09, 95% confidence interval (CI): 0.64-1.84) with similar estimated 28-day mortality in the COVACTA tocilizumab treatment arm compared with the external comparator arm (18%, 95% CI: 13-24 vs. 19%, 95% CI: 13-24, P > 0.9). COVACTA placebo treatment arm participants had a similar risk of mortality (adjusted HR: 0.69, 95% CI: 0.32-1.46) compared with the external comparator arm. Using an external comparator arm has the potential to supplement RCT data and support results of primary RCT analyses.

Latent Tuberculosis Infection Treatment Practices in Two Large Integrated Health Systems in California, 2009-2018.

Background: Treatment of latent tuberculosis infection (LTBI) is highly effective at preventing active tuberculosis (TB) disease. Understanding LTBI treatment practices in US health system settings is critical to identify opportunities to improve treatment prescription, initiation, and completion, and thus to prevent TB disease. Methods: We assessed LTBI treatment practices among a cohort of adults after their first positive LTBI test (tuberculin skin test [TST] or interferon gamma release assay [IGRA]) between 2009 and 2018 at 2 large integrated health systems in California. We described the prescription, initiation, and completion of LTBI treatment (isoniazid [INH], rifampin, and rifamycin-INH short-course combinations) by demographic and clinical characteristics. We used multivariable robust Poisson regression to examine factors that were independently associated with treatment prescription and completion. Results: Among 79 302 individuals with a positive LTBI test, 33.0% were prescribed LTBI treatment, 28.3% initiated treatment, and 18.5% completed treatment. Most individuals were prescribed INH (82.0%), but treatment completion was higher among those prescribed rifamycin-INH short-course combinations (69.6% for INH + rifapentine and 70.3% for INH + rifampin) compared with those prescribed INH (56.3%) or rifampin (56.6%). In adjusted analyses, treatment prescription and completion were associated with older age, female sex, more comorbidities, immunosuppression, not being born in a high-TB incidence country, and testing positive with IGRA vs TST. Conclusions: LTBI treatment is underutilized, requiring tailored interventions to support treatment prescription and completion for patients with LTBI.

An Atypical Presentation of Mpox Transmitted Between Transgender Men Through Oral Sex.

ABSTRACT: The current multicountry outbreak of mpox in 2022 is the first occurrence of widespread transmission in nonendemic countries. Prior cases in the United States involved exposure through foreign travel or direct contact with infected rodents. Reports of the current outbreak have predominately described spread through sexual encounters between cis-gender men who have sex with men. We report a unique case of mpox in which the transmission occurred through oral sex between 2 transgender men, with a short incubation period and progressive asynchronous emergence of lesions. Continued analysis of transmission routes and awareness will improve timely prevention, diagnosis and treatment.

Severe Acute Respiratory Syndrome Coronavirus 2 Delta Variant Genomic Variation Associated With Breakthrough Infection in Northern California: A Retrospective Cohort Study.

BACKGROUND: The association between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) genomic variation and breakthrough infection is not well defined among persons with Delta variant SARS-CoV-2 infection. METHODS: In a retrospective cohort, we assessed whether individual nonlineage defining mutations and overall genomic variation (including low-frequency alleles) were associated with breakthrough infection, defined as SARS-CoV-2 infection after coronavirus disease 2019 primary vaccine series. We identified all nonsynonymous single-nucleotide polymorphisms, insertions, and deletions in SARS-CoV-2 genomes with ≥5% allelic frequency and population frequency of ≥5% and ≤95%. Using Poisson regression, we assessed the association with breakthrough infection for each individual mutation and a viral genomic risk score. RESULTS: Thirty-six mutations met our inclusion criteria. Among 12 744 persons infected with Delta variant SARS-CoV-2, 5949 (47%) were vaccinated and 6795 (53%) were unvaccinated. Viruses with a viral genomic risk score in the highest quintile were 9% more likely to be associated with breakthrough infection than viruses in the lowest quintile, but including the risk score improved overall predictive model performance (measured by C statistic) by only +0.0006. CONCLUSIONS: Genomic variation within SARS-CoV-2 Delta variant was weakly associated with breakthrough infection, but several potential nonlineage defining mutations were identified that might contribute to immune evasion by SARS-CoV-2.

Influenza Vaccination Uptake and Associated Factors Among Adults With and Without Human Immunodeficiency Virus in a Large, Integrated Healthcare System.

BACKGROUND: Influenza vaccination is recommended for adults regardless of human immunodeficiency virus (HIV) status. There may be facilitators or barriers to vaccinating people with HIV (PWH) that differ from people without HIV (PWoH). We sought to describe the uptake of influenza vaccination by HIV status and identify factors associated with vaccination. METHODS: We abstracted data from the electronic health records of PWH and PWoH in Kaiser Permanente Northern California during 6 influenza seasons (2013-2018). We determined vaccination uptake and used Poisson regression models to evaluate factors associated with vaccination in PWH and PWoH. RESULTS: 9272 PWH and 194 393 PWoH matched by age, sex, and race/ethnicity were included (mean age: 48 vs 49 years; men: 91% vs 90%; White race: 53% for both groups). PWH were more likely to receive the influenza vaccine (65-69% across years for PWH and 37-41% for PWoH) with an adjusted risk ratio for all years of 1.48 (95% CI: 1.46-1.50). For PWH, lower vaccination uptake was associated with several factors that suggested more complex health needs, such as lower CD4 cell counts, higher HIV viral loads, prior depression diagnoses, having Medicare insurance, and having a higher number of comorbidities. Associations with vaccination uptake were attenuated in PWH, compared with PWoH, for smoking, alcohol, and demographic factors. CONCLUSIONS: PWH had an almost 50% higher uptake of influenza vaccination than PWoH, possibly reflecting greater engagement with the healthcare system. We also found that PWH with more complex health needs had reduced vaccination uptake. Findings may inform outreach strategies to increase influenza vaccination in PWH.

Patient-Reported Barriers to Treatment Initiation and Completion for Latent Tuberculosis Infection Among Patients Within a Large Integrated Health Care System in Southern California.

OBJECTIVE: More than 80% of active tuberculosis in the United States is due to reactivation of latent tuberculosis infection (LTBI), which can be prevented via screening and treatment. Treatment initiation and completion rates are low for patients with LTBI in the United States, and the barriers to successful treatment are poorly understood. DESIGN: We conducted semistructured qualitative interviews with 38 patients who were prescribed LTBI treatment (9 months isoniazid, 6 months rifampin, or 3 months rifamycin-isoniazid short-course combinations). We used purposeful sampling employing a maximum variation approach to obtain diverse perspectives of patients who did not initiate treatment, who did not complete treatment, and who completed treatment (n = 14, n = 16, and n = 8, respectively). Patients were asked about LTBI knowledge, experience regarding treatment, interactions with providers, and barriers they faced. Using a team coding model (2 coders/analysts), we developed deductively derived (a priori) codes based on our central research questions and inductively derived codes that emerged directly from the data. Analysis of our coding categories and relationships generated a hierarchy of key themes and subthemes. SETTING: Kaiser Permanente Southern California. PARTICIPANTS: Individuals 18 years or older who received a diagnosis of LTBI and prescribed treatment. MAIN OUTCOME MEASURES: LTBI knowledge, attitudes toward LTBI, attitudes toward LTBI treatment, attitudes toward providers, and explanation of barriers. RESULTS: Most patients reported having limited knowledge of LTBI. In addition to the duration of treatment, barriers to initiation and completion included perceived lack of support, uncomfortable side effects, and pervasive minimization of the positive impact of treatment on their health. Many patients felt there was little incentive to overcome barriers. CONCLUSIONS: Overall, patient experience with LTBI treatment initiation and completion could be improved with patient-centered treatment and more frequent follow-ups.

Human Immunodeficiency Virus Status, Tenofovir Exposure, and the Risk of Poor Coronavirus Disease 19 Outcomes: Real-World Analysis From 6 United States Cohorts Before Vaccine Rollout.

BACKGROUND: People with human immunodeficiency virus (HIV) (PWH) may be at increased risk for severe coronavirus disease 2019 (COVID-19) outcomes. We examined HIV status and COVID-19 severity, and whether tenofovir, used by PWH for HIV treatment and people without HIV (PWoH) for HIV prevention, was associated with protection. METHODS: Within 6 cohorts of PWH and PWoH in the United States, we compared the 90-day risk of any hospitalization, COVID-19 hospitalization, and mechanical ventilation or death by HIV status and by prior exposure to tenofovir, among those with severe acute respiratory syndrome coronavirus 2 infection between 1 March and 30 November 2020. Adjusted risk ratios (aRRs) were estimated by targeted maximum likelihood estimation, with adjustment for demographics, cohort, smoking, body mass index, Charlson comorbidity index, calendar period of first infection, and CD4 cell counts and HIV RNA levels (in PWH only). RESULTS: Among PWH (n = 1785), 15% were hospitalized for COVID-19 and 5% received mechanical ventilation or died, compared with 6% and 2%, respectively, for PWoH (n = 189 351). Outcome prevalence was lower for PWH and PWoH with prior tenofovir use. In adjusted analyses, PWH were at increased risk compared with PWoH for any hospitalization (aRR, 1.31 [95% confidence interval, 1.20-1.44]), COVID-19 hospitalizations (1.29 [1.15-1.45]), and mechanical ventilation or death (1.51 [1.19-1.92]). Prior tenofovir use was associated with reduced hospitalizations among PWH (aRR, 0.85 [95% confidence interval, .73-.99]) and PWoH (0.71 [.62-.81]). CONCLUSIONS: Before COVID-19 vaccine availability, PWH were at greater risk for severe outcomes than PWoH. Tenofovir was associated with a significant reduction in clinical events for both PWH and PWoH.

Differences in COVID-19 testing and adverse outcomes by race, ethnicity, sex, and health system setting in a large diverse US cohort.

BACKGROUND: Racial/ethnic disparities during the first six months of the COVID-19 pandemic led to differences in COVID-19 testing and adverse outcomes. We examine differences in testing and adverse outcomes by race/ethnicity and sex across a geographically diverse and system-based COVID-19 cohort collaboration. METHODS: Observational study among adults (≥18 years) within six US cohorts from March 1, 2020 to August 31, 2020 using data from electronic health record and patient reporting. Race/ethnicity and sex as risk factors were primary exposures, with health system type (integrated health system, academic health system, or interval cohort) as secondary. Proportions measured SARS-CoV-2 testing and positivity; attributed hospitalization and death related to COVID-19. Relative risk ratios (RR) with 95% confidence intervals quantified associations between exposures and main outcomes. RESULTS: 5,958,908 patients were included. Hispanic patients had the highest proportions of SARS-CoV-2 testing (16%) and positivity (18%), while Asian/Pacific Islander patients had the lowest portions tested (11%) and White patients had the lowest positivity rates (5%). Men had a lower likelihood of testing (RR = 0.90 [0.89-0.90]) and a higher positivity risk (RR = 1.16 [1.14-1.18]) compared to women. Black patients were more likely to have COVID-19-related hospitalizations (RR = 1.36 [1.28-1.44]) and death (RR = 1.17 [1.03-1.32]) compared with White patients. Men were more likely to be hospitalized (RR = 1.30 [1.16-1.22]) or die (RR = 1.70 [1.53-1.89]) compared to women. These racial/ethnic and sex differences were reflected in both health system types. CONCLUSIONS: This study supports evidence of disparities by race/ethnicity and sex during the COVID-19 pandemic that persisted even in healthcare settings with reduced barriers to accessing care. Further research is needed to understand and prevent the drivers that resulted in higher burdens of morbidity among certain Black patients and men.

Natural Language Processing for Improved Characterization of COVID-19 Symptoms: Observational Study of 350,000 Patients in a Large Integrated Health Care System.

BACKGROUND: Natural language processing (NLP) of unstructured text from electronic medical records (EMR) can improve the characterization of COVID-19 signs and symptoms, but large-scale studies demonstrating the real-world application and validation of NLP for this purpose are limited. OBJECTIVE: The aim of this paper is to assess the contribution of NLP when identifying COVID-19 signs and symptoms from EMR. METHODS: This study was conducted in Kaiser Permanente Southern California, a large integrated health care system using data from all patients with positive SARS-CoV-2 laboratory tests from March 2020 to May 2021. An NLP algorithm was developed to extract free text from EMR on 12 established signs and symptoms of COVID-19, including fever, cough, headache, fatigue, dyspnea, chills, sore throat, myalgia, anosmia, diarrhea, vomiting or nausea, and abdominal pain. The proportion of patients reporting each symptom and the corresponding onset dates were described before and after supplementing structured EMR data with NLP-extracted signs and symptoms. A random sample of 100 chart-reviewed and adjudicated SARS-CoV-2-positive cases were used to validate the algorithm performance. RESULTS: A total of 359,938 patients (mean age 40.4 [SD 19.2] years; 191,630/359,938, 53% female) with confirmed SARS-CoV-2 infection were identified over the study period. The most common signs and symptoms identified through NLP-supplemented analyses were cough (220,631/359,938, 61%), fever (185,618/359,938, 52%), myalgia (153,042/359,938, 43%), and headache (144,705/359,938, 40%). The NLP algorithm identified an additional 55,568 (15%) symptomatic cases that were previously defined as asymptomatic using structured data alone. The proportion of additional cases with each selected symptom identified in NLP-supplemented analysis varied across the selected symptoms, from 29% (63,742/220,631) of all records for cough to 64% (38,884/60,865) of all records with nausea or vomiting. Of the 295,305 symptomatic patients, the median time from symptom onset to testing was 3 days using structured data alone, whereas the NLP algorithm identified signs or symptoms approximately 1 day earlier. When validated against chart-reviewed cases, the NLP algorithm successfully identified signs and symptoms with consistently high sensitivity (ranging from 87% to 100%) and specificity (94% to 100%). CONCLUSIONS: These findings demonstrate that NLP can identify and characterize a broad set of COVID-19 signs and symptoms from unstructured EMR data with enhanced detail and timeliness compared with structured data alone.

Analysis of Severe Illness After Postvaccination COVID-19 Breakthrough Among Adults With and Without HIV in the US.

Importance: Understanding the severity of postvaccination SARS-CoV-2 (ie, COVID-19) breakthrough illness among people with HIV (PWH) can inform vaccine guidelines and risk-reduction recommendations. Objective: To estimate the rate and risk of severe breakthrough illness among vaccinated PWH and people without HIV (PWoH) who experience a breakthrough infection. Design, Setting, and Participants: In this cohort study, the Corona-Infectious-Virus Epidemiology Team (CIVET-II) collaboration included adults (aged ≥18 years) with HIV who were receiving care and were fully vaccinated by June 30, 2021, along with PWoH matched according to date fully vaccinated, age group, race, ethnicity, and sex from 4 US integrated health systems and academic centers. Those with postvaccination COVID-19 breakthrough before December 31, 2021, were eligible. Exposures: HIV infection. Main Outcomes and Measures: The main outcome was severe COVID-19 breakthrough illness, defined as hospitalization within 28 days after a breakthrough SARS-CoV-2 infection with a primary or secondary COVID-19 discharge diagnosis. Discrete time proportional hazards models estimated adjusted hazard ratios (aHRs) and 95% CIs of severe breakthrough illness within 28 days of breakthrough COVID-19 by HIV status adjusting for demographic variables, COVID-19 vaccine type, and clinical factors. The proportion of patients who received mechanical ventilation or died was compared by HIV status. Results: Among 3649 patients with breakthrough COVID-19 (1241 PWH and 2408 PWoH), most were aged 55 years or older (2182 patients [59.8%]) and male (3244 patients [88.9%]). The cumulative incidence of severe illness in the first 28 days was low and comparable between PWoH and PWH (7.3% vs 6.7%; risk difference, -0.67%; 95% CI, -2.58% to 1.23%). The risk of severe breakthrough illness was 59% higher in PWH with CD4 cell counts less than 350 cells/µL compared with PWoH (aHR, 1.59; 95% CI, 0.99 to 2.46; P = .049). In multivariable analyses among PWH, being female, older, having a cancer diagnosis, and lower CD4 cell count were associated with increased risk of severe breakthrough illness, whereas previous COVID-19 was associated with reduced risk. Among 249 hospitalized patients, 24 (9.6%) were mechanically ventilated and 20 (8.0%) died, with no difference by HIV status. Conclusions and Relevance: In this cohort study, the risk of severe COVID-19 breakthrough illness within 28 days of a breakthrough infection was low among vaccinated PWH and PWoH. PWH with moderate or severe immune suppression had a higher risk of severe breakthrough infection and should be included in groups prioritized for additional vaccine doses and risk-reduction strategies.

Retrospective cohort study to assess the association between treatment with tocilizumab and mortality among mechanically ventilated patients with COVID-19.

OBJECTIVES: Assess the association between tocilizumab administration and clinical outcomes among mechanically ventilated patients with COVID-19 pneumonia. DESIGN: Retrospective cohort study. SETTING: Large integrated health system with 9 million members in California, USA. PARTICIPANTS: 4185 Kaiser Permanente members hospitalised with COVID-19 pneumonia requiring invasive mechanical ventilation (IMV). INTERVENTIONS: Receipt of tocilizumab within 10 days of initiation of IMV. OUTCOME MEASURES: Using a retrospective cohort of consecutive patients hospitalised with COVID-19 pneumonia who required IMV in a large integrated health system in California, USA, we assessed the association between tocilizumab administration and 28-day mortality, time to extubation from IMV and time to hospital discharge. RESULTS: Among 4185 patients, 184 received tocilizumab and 4001 patients did not receive tocilizumab within 10 days of initiation of IMV. After inverse probability weighting, baseline characteristics were well balanced between groups. Patients treated with tocilizumab had a similar risk of death in the 28 days after intubation compared with patients not treated with tocilizumab (adjusted HR (aHR), 1.21, 95% CI 0.98 to 1.50), but did have a significantly longer time-to-extubation (aHR 0.71; 95% CI 0.57 to 0.88) and time-to-hospital-discharge (aHR 0.66; 95% CI 0.50 to 0.88). However, patients treated with tocilizumab ≤2 days after initiation of IMV had a similar risk of mortality (aHR 1.47; 95% CI 0.96 to 2.26), but significantly shorter time-to-extubation (aHR 0.37; 95% CI 0.23 to 0.58) and time-to-hospital-discharge (aHR 0.31; 95% CI CI 0.17 to 0.56) compared with patients treated with tocilizumab 3-10 days after initiation of IMV. CONCLUSIONS: Among mechanically ventilated patients with COVID-19, the risk of death in the 28-day follow-up period was similar, but time-to-extubation and time-to-hospital-discharge were longer in patients who received tocilizumab within 10 days of initiation of IMV compared with patients who did not receive tocilizumab.

Development and validation of a prediction algorithm to identify birth in countries with high tuberculosis incidence in two large California health systems.

OBJECTIVE: Though targeted testing for latent tuberculosis infection ("LTBI") for persons born in countries with high tuberculosis incidence ("HTBIC") is recommended in health care settings, this information is not routinely recorded in the electronic health record ("EHR"). We develop and validate a prediction model for birth in a HTBIC using EHR data. MATERIALS AND METHODS: In a cohort of patients within Kaiser Permanente Southern California ("KPSC") and Kaiser Permanent Northern California ("KPNC") between January 1, 2008 and December 31, 2019, KPSC was used as the development dataset and KPNC was used for external validation using logistic regression. Model performance was evaluated using area under the receiver operator curve ("AUCROC") and area under the precision and recall curve ("AUPRC"). We explored various cut-points to improve screening for LTBI. RESULTS: KPSC had 73% and KPNC had 54% of patients missing country-of-birth information in the EHR, leaving 2,036,400 and 2,880,570 patients with EHR-documented country-of-birth at KPSC and KPNC, respectively. The final model had an AUCROC of 0.85 and 0.87 on internal and external validation datasets, respectively. It had an AUPRC of 0.69 and 0.64 (compared to a baseline HTBIC-birth prevalence of 0.24 at KPSC and 0.19 at KPNC) on internal and external validation datasets, respectively. The cut-points explored resulted in a number needed to screen from 7.1-8.5 persons/positive LTBI diagnosis, compared to 4.2 and 16.8 persons/positive LTBI diagnosis from EHR-documented birth in a HTBIC and current screening criteria, respectively. DISCUSSION: Using logistic regression with EHR data, we developed a simple yet useful model to predict birth in a HTBIC which decreased the number needed to screen compared to current LTBI screening criteria. CONCLUSION: Our model improves the ability to screen for LTBI in health care settings based on birth in a HTBIC.